Vytaute (aka VK) is a data analyst. Prior to joining Amey in November 2017, she applied machine learning, GIS and social network analysis skills in business information, marketing and education sectors.
During her Master’s in Data Science degree, VK’s research focused on applying machine learning techniques on audio feature data. This work lead to a scientific paper presented at the 18th International Society for Music Information Retrieval Conference in China (October 2017).
Since joining Amey VK has worked with the Network Rail Telecommunications asset team to produce asset degradation models for Tier 2 whole life cost modelling. Building on understanding of the failure mechanisms and rates of different equipment, VK built degradation models for a number of assets, such as transmission and GSM-Rail.
VK was also part of a team conducting a review of Heathrow Airport asset maintenance task schedules. The project aimed to rationalise and consolidate over 1000 job plans using a high level of stakeholder engagement to draw out asset knowledge. Within this project VK has been responsible for leading review workshops to develop improved maintenance strategies for mechanical asset systems.